July 9, 2025 | BOMA International, Ella Krygiel
At the 2025 BOMA International Annual Conference in Boston, MA, a consistent theme across educational sessions was the pace of technological change – and how industrial real estate must keep up. During the session, “The Future of BEPS: Navigating Regulatory Changes & Market Trends,” panelists Stuart Feilden, Strategic Partner Manager, Siemens SI-Buildings and Eshaan Mathew, Business Development Manager, Smart Infrastructure – Buildings discussed how legacy systems in industrial buildings are increasingly at odds with the demands of today’s data-driven economy. They used examples like data centers and vehicle telematics to show how many industrial buildings still rely on siloed, outdated systems, while other sectors are moving toward integration and automation.
This is especially relevant given projections from ABI Research, which estimate the number of public data centers will grow from 6,111 in 2025 to 8,378 by 2030. To keep pace with that demand, data centers and the facilities that support them must modernize their infrastructure.
As Mathew noted, many facilities are trapped in a “never-ending cycle of reacting to issues,” where decisions are based on siloed data rather than forward-looking insights.
Let’s break that down into more detail. According to The Technology Square, there are several hidden costs of clinging to legacy data centers such as:
- Maintenance Money Pit: Even if your legacy data center “still works,” keeping it operational is costly. As hardware ages, replacement parts become scarce and expensive.
- Security Risks: Outdated systems often lack current software patches, leaving them vulnerable to cyber threats and compliance risks.
- Scaling Struggles: Legacy systems weren’t built for the cloud era. This means slower time to market, stifled innovation and missed opportunities.
- Lack of Innovation: New technologies like AI and real-time analytics require modern environments. Legacy systems simply can’t support them.
Modernization isn’t just about hardware. It’s about how buildings process and analyze data. Feilden explained, “The development of the Cloud has really affected the smart building market.” Buildings gives a few reasons why these technologies are so integral:
- Connectivity: Cloud-based platforms enable real-time data flow, giving operators visibility and insight across facilities.
- Efficiency: AI-enabled smart buildings can securely process and store data within the operator’s own network.
- Feedback loop: The integration of AI, IoT and cloud technology creates a continuous improvement cycle—identifying inefficiencies and recommending strategic actions.
That’s why system consolidation is so important. Many building operators still rely on fragmented platforms. Feilden pointed to the evolution of the iPhone as a useful analogy:
“We’ve come a long way [with technology]. The iPhone was released in 2007,” he said. Smart phones, vehicle telematics and data center information management (DCMI) software are now standard in many industries. “Most people have legacy systems that are consolidating. In the smart building industry, we have many software platforms that are transitioning to open use cases – following the same journey as the iPhone.”
Feilden compared the rise of smart buildings to the adoption curve of smartphones: what was once niche is now essential. He also noted the increasing presence of self-driving vehicles as further proof that multiple data sets are converging into unified platforms.
So, how does this impact the data centers specifically? As technologies like AI become more advanced—and more embedded in day-to-day business—data centers must scale to support increased power and performance demands.
Feilden gave a timely example: “ChatGPT will have been in the market for three years now in fall 2025.” The rapid evolution of generative AI tools reflects just how fast the built environment must adapt. According to Bloom Energy, some data center racks now require up to 50kW of power, far exceeding the capabilities of traditional air-cooling systems. That’s why modern approaches like liquid cooling are increasingly preferred to manage heat in higher-density deployments.
In this context, industrial buildings, particularly those supporting digital infrastructure, must be capable of handling these new technical loads. That includes everything from updated electrical systems to integrated HVAC, environmental sensors, and automation platforms.
Due to this impressive growth, technology is enabling the convergence of IT, IoT and OT. This is where reliability-centered maintenance is no longer something to aim for in the future; it’s becoming a current expectation. This can include everything from sensor technology to help monitor systems, to the growing use of fault detection and diagnostics.
As Mathew and Feilden discussed, these technologies have been around in some form since the 1960s, but the difference now is how cloud-based platforms are making them more accessible, scalable and powerful. What used to be seen as “extra” is quickly becoming essential to keep up with changing market demands.
As Feilden put it, “You cannot optimize something that’s broken. That’s where diagnostic practice is essential. We need to monitor and track how these systems are going. Understand where the market is going and knowing how to adapt.”
Mathew added to this, pointing out that many industrial buildings are still stuck in a loop of reacting to problems instead of preventing them. Breaking out of that cycle requires moving away from siloed data and toward smarter, more connected systems that support real-time decision-making.
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